Docker images#

We provide docker images to be able to test TTS without having to setup your own environment.

Using premade images#

You can use premade images built automatically from the latest TTS version.

CPU version#

docker pull ghcr.io/coqui-ai/tts-cpu

GPU version#

docker pull ghcr.io/coqui-ai/tts

Building your own image#

docker build -t tts .

Basic inference#

Basic usage: generating an audio file from a text passed as argument. You can pass any tts argument after the image name.

CPU version#

docker run --rm -v ~/tts-output:/root/tts-output ghcr.io/coqui-ai/tts-cpu --text "Hello." --out_path /root/tts-output/hello.wav

GPU version#

For the GPU version, you need to have the latest NVIDIA drivers installed. With nvidia-smi you can check the CUDA version supported, it must be >= 11.8

docker run --rm --gpus all -v ~/tts-output:/root/tts-output ghcr.io/coqui-ai/tts --text "Hello." --out_path /root/tts-output/hello.wav --use_cuda true

Start a server#

Starting a TTS server: Start the container and get a shell inside it.

CPU version#

docker run --rm -it -p 5002:5002 --entrypoint /bin/bash ghcr.io/coqui-ai/tts-cpu
python3 TTS/server/server.py --list_models #To get the list of available models
python3 TTS/server/server.py --model_name tts_models/en/vctk/vits 

GPU version#

docker run --rm -it -p 5002:5002 --gpus all --entrypoint /bin/bash ghcr.io/coqui-ai/tts
python3 TTS/server/server.py --list_models #To get the list of available models
python3 TTS/server/server.py --model_name tts_models/en/vctk/vits --use_cuda true

Click there and have fun with the server!